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Presentation

High-Assurance Software

HASLab is focused on the design and implementation of high-assurance software systems: software that is correct by design and resilient to environment faults and malicious attacks. 

To accomplish this mission, HASLab covers three main competences — Cybersecurity, Distributed Systems, and Software Engineering — complemented by other competences such as Human-Computer Interaction, Programming Languages, or the Mathematics of Computing. 

Software Engineering – methods, techniques, and tools for rigorous software development, that can be applied to the internal functionality of a component, its composition with other components, as well as the interaction with the user.

Distributed Systems – improving the reliability and scalability of software, by exploring properties inherent to the distribution and replication of computer systems.

Cybersecurity – minimize the vulnerability of software components to hostile attacks, by deploying structures and cryptographic protocols whose security properties are formally proven.

Through a multidisciplinary approach that is based on solid theoretical foundations, we aim to provide solutions — theory, methods, languages, tools — for the development of complete ICT systems that provide strong guarantees to their owners and users. Prominent application areas of HASLab research include the development of safety and security critical software systems, the operation of secure cloud infrastructures, and the privacy-preserving management and processing of big data.

Latest News

Researcher explores the versatility of partitioned Bloom Filters in the design of data structures

The study by Paulo Sérgio Almeida, INESC TEC researcher and professor at the University of Minho, focuses on Bloom Filters, a very popular probabilistic data structure in the design of databases, distributed systems, and communication networks. The study, which demonstrates the versatility of partitioned Bloom Filters, was accepted for publication in IEEE Transactions on Computers, one of the top journals in Informatics and Computing.

29th November 2022

INESC TEC research on Alloy specification language presented at top software engineering conference

A team of INESC TEC researchers working on the Alloy language and specification tool presented the QAlloy extension at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), a top conference in the area of software engineering that took place between November 14 and 18, in Singapore.

22nd November 2022

RISC2 project acknowledged by international journal specialised in advanced computing

The RISC2 project, which aims to promote and improve the relationship between research and innovation communities in Europe and Latin America, won the HPCwire Editor’s Choice Awards in the category of Best HPC Collaboration.

21st November 2022

INESC TEC welcomed students at the “Verão no Campus” in Braga

Close to 20 high school students visited INESC TEC’s High-assurance Software Laboratory (HASLab). The visit took place within the scope of the “Computação sem Fronteiras” initiative, one of several activities part of the “Verão no Campus” – promoted by the University of Minho; the activities took place between July 18 and 22, in the Department of Informatics (DI) of the University of Minho, Braga.  

28th July 2022

INESC TEC and UMinho welcomed Haim Levkowitz, a leading expert in the field of computing

The Chair of the Computer Science Department at the Massachusetts Lowell University, Haim Levkowitz, visited INESC TEC and the University of Minho, on May 20, 23 and 25, respectively, under the Staff Mobility for Teaching of the Erasmus+ programme.

26th May 2022

060

Projects

exaSIMPLE

exaSIMPLE: A Hybrid ML-CFD SIMPLE Algorithm for the Exascale Era

2024-2025

Saude24GB

Linha de Saúde 24h da Guiné-Bissau

2024-2024

EPICURE

High-level specialised application support service in High-Performance Computing (HPC)

2024-2028

TwinEU

Digital Twin for Europe

2024-2026

HANAMI

Hpc AlliaNce for Applications and supercoMputing Innovation: the Europe - Japan collaboration

2024-2026

ENSCOMP3

Ensino de Ciência da Computação nas Escolas 3

2023-2025

AzDIH

Azores Digital Innovation Hub on Tourism and Sustainability

2023-2025

PFAI4_4eD

Programa de Formação Avançada Industria 4 - 4a edição

2023-2023

ATE

Alliance for Energy Transition

2023-2025

Green_Dat_AI

Energy-efficient AI-ready Data Spaces

2023-2025

EuroCC2

National Competence Centres in the framework of EuroHPC Phase 2

2023-2025

fMP

Formação de Introdução à utilização de recursos HPC (Técnicas básicas de Programação Paralela)

2022-2022

AURORA

Deteção de atividade no interior do veículo

2022-2023

NewSpacePortugal

Agenda New Space Portugal

2022-2025

ATTRACT_DIH

Digital Innovation Hub for Artificial Intelligence and High-Performance Computing

2022-2025

BeFlexible

Boosting engagement to increase flexibility

2022-2026

ENERSHARE

European commoN EneRgy dataSpace framework enabling data sHaring-driven Across- and beyond- eneRgy sErvices

2022-2025

Gridsoft

Parecer sobre a implementação de software para redes elétricas inteligentes

2022-2022

PFAI4_3ed

Programa de Formação Avançada Industria 4 - 3a edição

2022-2022

THEIA

Automated Perception Driving

2022-2023

SpecRep

Constraint-based Specification Repair

2022-2023

IBEX

Métodos quantitativos para a programação ciber-física: Uma abordagem precisa para racicionar sobre imprecisões na computação ciber-física

2022-2024

FLEXCOMM

Towards Energy-aware Communications: Connecting the power grid and communication infrastructure

2022-2023

STDCNCS

Desenvolvimento de estudo sobre a comunidade de cibersegurança em Portugal, no âmbito do Observatório de Cibersegurança

2021-2023

Sustainable HPC

Computação de elevado desempenho sustentável

2021-2025

CircThread

Building the Digital Thread for Circular Economy Product, Resource & Service Management

2021-2025

PassCert

Exploring the Impact of Formal Verification on the Adoption of Password Security Software

2021-2022

IoT4Distribuicao

Análise de Requisitos e Especificação Funcional de uma Arquitetura Distribuída baseada em soluções IoT para a Gestão e Controlo da Rede de Distribuição

2021-2023

RISC2

A network for supporting the coordination of High-Performance Computing research between Europe and Latin America

2021-2023

CloudAnalytics4Dams

Gestão de Grandes Quantidades de Dados em Barragens da EDP Produção

2021-2021

PAStor

Programmable and Adaptable Storage for AI-oriented HPC Ecosystems

2020-2021

PFAI4.0

Programa de Formação Avançada Industria 4.0

2020-2021

Collaboration

Collaborative Visual Development

2020-2021

AIDA

Adaptive, Intelligent and Distributed Assurance Platform

2020-2023

BigHPC

A Management Framework for Consolidated Big Data and HPC

2020-2023

SLSNA

Prestação de Serviços no ambito do projeto SKORR

2020-2021

AppOwl

Deteção de Mutações Maliciosas no Browser

2020-2021

InterConnect

Interoperable Solutions Connecting Smart Homes, Buildings and Grids

2019-2024

T4CDTKC

Training 4 Cotec, Digital Transformation Knowledge Challenge - Elaboração de Programa de Formação “CONHECER E COMPREENDER O DESAFIO DAS TECNOLOGIAS DE TRANSFORMAÇÃO DIGITAL”

2019-2021

CLOUD4CANDY

Cloud for CANDY

2019-2019

HADES

HArdware-backed trusted and scalable DEcentralized Systems

2018-2022

MaLPIS

Aprendizagem Automática para Deteção de Ataques e Identificação de Perfis Segurança na Internet

2018-2022

SKORR

Advancing the Frontier of Social Media Management Tools

2018-2021

DaVinci

Distributed architectures: variability and interaction for cyber-physical systems

2018-2022

SAFER

Safery verification for robotic software

2018-2021

KLEE

Coalgebraic modeling and analysis for computational synthetic biology

2018-2021

InteGrid

Demonstration of INTElligent grid technologies for renewables INTEgration and INTEractive consumer participation enabling INTEroperable market solutions and INTErconnected stakeholders

2017-2020

Lightkone

Lightweight Computation for Networks at the Edge

2017-2019

CloudDBAppliance

European Cloud In-Memory Database Appliance with Predictable Performance for Critical Applications

2016-2019

GSL

GreenSoftwareLab: Towards an Engineering Discipline for Green Software

2016-2019

Cloud-Setup

PLATAFORMA DE PREPARAÇÃO DE CONTEÚDOS AUDIOVISUAIS PARA INGEST NA CLOUD

2016-2019

CORAL-TOOLS

CORAL – Sustainable Ocean Exploitation: Tools and Sensors

2016-2018

SafeCloud

Secure and Resilient Cloud Architecture

2015-2018

NanoStima-RL1

NanoSTIMA - Macro-to-Nano Human Sensing Technologies

2015-2019

NanoStima-RL3

NanoSTIMA - Health data infrastructure

2015-2019

SMILES

SMILES - Smart, Mobile, Intelligent and Large scale Sensing and analytics

2015-2019

UPGRID

Real proven solutions to enable active demand and distributed generation flexible integration, through a fully controllable LOW Voltage and medium voltage distribution grid

2015-2017

LeanBigData

Ultra-Scalable and Ultra-Efficient Integrated and Visual Big Data Analytics

2014-2017

Practice

Privacy-Preserving Computation in the Cloud

2013-2016

CoherentPaaS

A Coherent and Rich PaaS with a Common Programming Model

2013-2016

Team
001

Laboratory

CLOUDinha

Publications

HASLab Publications

View all Publications

2023

Probabilistic Causal Contexts for Scalable CRDTs

Authors
Fernandes, PH; Baquero, C;

Publication
Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data, PaPoC 2023, Rome, Italy, 8 May 2023

Abstract

2023

A Year Embedded in the Crypto-NFT Space

Authors
Baquero, C;

Publication
COMMUNICATIONS OF THE ACM

Abstract

2023

Consistent comparison of symptom-based methods for COVID-19 infection detection

Authors
Rufino, J; Ramirez, JM; Aguilar, J; Baquero, C; Champati, J; Frey, D; Lillo, RE; Fernandez Anta, A;

Publication
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

Abstract
Background: During the global pandemic crisis, various detection methods of COVID-19-positive cases based on self-reported information were introduced to provide quick diagnosis tools for effectively planning and managing healthcare resources. These methods typically identify positive cases based on a particular combination of symptoms, and they have been evaluated using different datasets.Purpose: This paper presents a comprehensive comparison of various COVID-19 detection methods based on self-reported information using the University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), a large health surveillance platform, which was launched in partnership with Facebook.Methods: Detection methods were implemented to identify COVID-19-positive cases among UMD-CTIS participants reporting at least one symptom and a recent antigen test result (positive or negative) for six countries and two periods. Multiple detection methods were implemented for three different categories: rule-based approaches, logistic regression techniques, and tree-based machine-learning models. These methods were evaluated using different metrics including F1-score, sensitivity, specificity, and precision. An explainability analysis has also been conducted to compare methods.Results: Fifteen methods were evaluated for six countries and two periods. We identify the best method for each category: rule-based methods (F1-score: 51.48% -71.11%), logistic regression techniques (F1-score: 39.91% -71.13%), and tree-based machine learning models (F1-score: 45.07% -73.72%). According to the explainability analysis, the relevance of the reported symptoms in COVID-19 detection varies between countries and years. However, there are two variables consistently relevant across approaches: stuffy or runny nose, and aches or muscle pain.Conclusions: Regarding the categories of detection methods, evaluating detection methods using homogeneous data across countries and years provides a solid and consistent comparison. An explainability analysis of a tree-based machine-learning model can assist in identifying infected individuals specifically based on their relevant symptoms. This study is limited by the self-report nature of data, which cannot replace clinical diagnosis.

2023

Efficient Embedding of Strategic Attribute Grammars via Memoization

Authors
Macedo, JN; Rodrigues, E; Viera, M; Saraiva, J;

Publication
Proceedings of the 2023 ACM SIGPLAN International Workshop on Partial Evaluation and Program Manipulation, PEPM 2023, Boston, MA, USA, January 16-17, 2023

Abstract

2023

Exploring Data Analysis and Visualization Techniques for Project Tracking: Insights from the ITC

Authors
Barrocas, AN; da Silva, AR; Saraiva, J;

Publication
Quality of Information and Communications Technology - 16th International Conference, QUATIC 2023, Aveiro, Portugal, September 11-13, 2023, Proceedings

Abstract
Data analysis has emerged as a cornerstone in facilitating informed decision-making across myriad fields, in particular in software development and project management. This integrative practice proves instrumental in enhancing operational efficiency, cutting expenditures, mitigating potential risks, and delivering superior results, all while sustaining structured organization and robust control. This paper presents ITC, a synergistic platform architected to streamline multi-organizational and multi-workspace collaboration for project management and technical documentation. ITC serves as a powerful tool, equipping users with the capability to swiftly establish and manage workspaces and documentation, thereby fostering the derivation of invaluable insights pivotal to both technical and business-oriented decisions. ITC boasts a plethora of features, from support for a diverse range of technologies and languages, synchronization of data, and customizable templates to reusable libraries and task automation, including data extraction, validation, and document automation. This paper also delves into the predictive analytics aspect of the ITC platform. It demonstrates how ITC harnesses predictive data models, such as Random Forest Regression, to anticipate project outcomes and risks, enhancing decision-making in project management. This feature plays a critical role in the strategic allocation of resources, optimizing project timelines, and promoting overall project success. In an effort to substantiate the efficacy and usability of ITC, we have also incorporated the results and feedback garnered from a comprehensive user assessment conducted in 2022. The feedback suggests promising potential for the platform’s application, setting the stage for further development and refinement. The insights provided in this paper not only underline the successful implementation of the ITC platform but also shed light on the transformative impact of predictive analytics in information systems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Facts & Figures

0Book Chapters

2020

68Researchers

2016

4Papers in indexed journals

2020

Contacts